skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Making It Spatial Makes It Personal: Engaging Stakeholders with Geospatial Participatory Modeling
Participatory research methods are increasingly used to collectively understand complex social-environmental problems and to design solutions through diverse and inclusive stakeholder engagement. But participatory research rarely engages stakeholders to co-develop and co-interpret models that conceptualize and quantify system dynamics for comparing scenarios of alternate action. Even fewer participatory projects have engaged people using geospatial simulations of dynamic landscape processes and spatially explicit planning scenarios. We contend that geospatial participatory modeling (GPM) can confer multiple benefits over non-spatial approaches for participatory research processes, by (a) personalizing connections to problems and their solutions through visualizations of place, (b) resolving abstract notions of landscape connectivity, and (c) clarifying the spatial scales of drivers, data, and decision-making authority. We illustrate through a case study how GPM is bringing stakeholders together to balance population growth and conservation in a coastal region facing dramatic landscape change due to urbanization and sea level rise. We find that an adaptive, iterative process of model development, sharing, and revision drive innovation of methods and ultimately improve the realism of land change models. This co-production of knowledge enables all participants to fully understand problems, evaluate the acceptability of trade-offs, and build buy-in for management actions in the places where they live and work.  more » « less
Award ID(s):
1737563
PAR ID:
10126154
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Land
Volume:
8
Issue:
2
ISSN:
2073-445X
Page Range / eLocation ID:
38
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Addressing “wicked” problems like urban stormwater management necessitates building shared understanding among diverse stakeholders with the influence to enact solutions cooperatively. Fuzzy cognitive maps (FCMs) are participatory modeling tools that enable diverse stakeholders to articulate the components of a socio-environmental system (SES) and describe their interactions. However, the spatial scale of an FCM is rarely explicitly considered, despite the influence of spatial scale on SES. We developed a technique to couple FCMs with spatially explicit survey data to connect stakeholder conceptualization of urban stormwater management at a regional scale with specific stormwater problems they identified. We used geospatial data and flooding simulation models to quantitatively evaluate stakeholders’ descriptions of location-specific problems. We found that stakeholders used a wide variety of language to describe variables in their FCMs and that government and academic stakeholders used significantly different suites of variables. We also found that regional FCM did not downscale well to concerns at finer spatial scales; variables and causal relationships important at location-specific scales were often different or missing from the regional FCM. This study demonstrates the spatial framing of stormwater problems influences the perceived range of possible problems, barriers, and solutions through spatial cognitive filtering of the system’s boundaries. 
    more » « less
  2. While stakeholder-driven approaches have been increasingly used in scenario modeling, previous studies have mostly focused on the qualitative elements, e.g., narratives and policy documents, from the stakeholders, but lack engagement of stakeholders with quantitative inputs. In this study, we conducted workshops with a stakeholder group to integrate the participatory mapping of future policies in the simulation, and to compare the environmental impacts after including the participatory mapping. A land system change model named CLUMondo was used to simulate four scenarios, i.e., Business-As-Usual (BAU), Destroying Resources in Owyhee (DRO), Ecological Conservation (EC), and Managed Recreation (MR), in Owyhee County, Idaho, United States. The InVEST models were used to assess water yield, soil erosion, and wildlife habitat under the four scenarios. The results show that the DRO scenario would decrease shrubland and increased grassland, thus leading to less water yield, more soil erosion, and deteriorated wildlife habitat anticipated through to 2050. On the contrary, the EC and MR scenarios reverse the trend and would improve these ecosystem services over the same time horizon. The stakeholder-driven policies appear to influence the spatial distribution of the land system and ecosystem services. The results help to reach a nuanced understanding of the stakeholder-driven scenarios and highlight the importance of engaging stakeholders in scenario modeling and environmental impact analysis. 
    more » « less
  3. Understanding and modeling the trajectories of change in broad level interactions in food-energy-water systems is incomplete when it is undertaken by researchers in isolation from those who live and work in the systems. For models and outcomes to have validity they need to be subjected to sustained development and iteration with stakeholders. This requires a paradigm shift in our thinking of stakeholder engagement from viewing such engagement as an isolated activity or part of the data collection methods to thinking of engagement as a process of knowledge generation. That process hinges on building relationships and building trust, and also sustaining these as long-term relationships through multiple elements of research design and execution. Using the case-study of a mid-size river basin we demonstrate a co-production of knowledge process for food-energy-water systems. The findings highlight the multiple and different ways in which knowledge co-production can be transacted in food-energy-water systems while also generating solutions to the use and re-use of water, energy, and nutrients at the landscape level. 
    more » « less
  4. This thesis explores geospatial vector data, including geometric shapes such as points, lines, and polygons. This data is crucial in navigation, urban planning, and many more applications. Geospatial computing is a multidisciplinary field that focuses on creating techniques and tools to handle large geospatial datasets. Given the reliance on data lakes to store large data sets in their raw formats, it is critical to have full support for geospatial datasets to enable scalable processing. To address this, we make two contributions in this area. First, we propose a column-oriented binary format called Spatial Parquet, which integrates geospatial vector data into Apache Parquet that enables significant data compression and efficient querying. Second, to improve support for semi-structured data, we introduce a distributed JSON processor for scalable SQL queries on large JSON datasets, including GeoJSON. It processes complex datasets like Open Street Map with features such as projection and filter push-down. Advances in Deep Learning (DL), including foundation models and Large Language Models (LLMs), offer opportunities for geospatial data analysis. We make three main contributions in this area. First, we study how to design DL models that can express a wide range of geospatial functions. We explore three representations: an image-based representa- tion using geo-referenced histograms (GeoImg), a graph-based point-set representation (Ge- oGraph), and a vector-based representation using a Fourier encoder (GeoVec). We formal- ize these representations and design corresponding models: ResNet and UNet for the first, PointNet++ for the second, and Poly2Vec with Transformers for the third. We evaluate all approaches on four spatial problems, showing the accuracy and effectiveness of the three approaches. Second, we create a benchmark called GS-QA for evaluating spatial question- answering with LLMs. A semi-automated process generates diverse question-answer pairs that cover various spatial objects, predicates, and complexities. An evaluation methodology is suggested with some experiments. Finally, a prototype for generating geospatial vector data from text prompts, called GeoGen I, is proposed. It has potential for applications such as spatial interpolation, data augmentation, and change analysis. We adapt diffusion models, traditionally used for generating realistic images, as geospatial data generators. We also explore their use for similarity search through geospatial data embeddings, highlighting the potential of vector databases in this domain. This thesis advances geospatial data processing, storage, analysis, and generation, opening new research pathways in geospatial computing. 
    more » « less
  5. This paper presents an overview of the integration of participatory processes in the production of official data. Through a series of interviews with strategic stakeholders we identified the key elements to institutionalize citizen science in the production of geospatial information. This article discusses practical contexts of uses of data produced or complemented by citizens in Mexico. We analyze institutional processes that facilitates or make difficult the integration into official mechanisms for generating more accurate cartographic information in various institutions, focusing on its possible adoption, in particular by the National Institute of Statistics and Geography (INEGI) of Mexico. Resources, data integration models, workflows, and an organizational structure are needed to benefit from citizen science. We find that the adoption of citizen science within an organization is subject to a well-defined and structured interest driven by leadership and implemented collectively. This presents a paradigm shift in obtaining information, citizen science as official data through concrete and functional information products will allow end users to benefit from timely and accurate data. The purpose of this article is then to generate organizational knowledge on how to use citizen science in public institutions, with long-term perspective, to mediate the lack of current and accurate spatial data and participate in social innovation. 
    more » « less